• DocumentCode
    1985601
  • Title

    Adaptive neuro-fuzzy inference system for speckle noise reduction in SAR images

  • Author

    Basturk, Alper ; Yuksel, M. Emin

  • Author_Institution
    Dept. of Comput. Eng., Erciyes Univ., Kayseri
  • fYear
    2007
  • fDate
    12-15 Feb. 2007
  • Firstpage
    1
  • Lastpage
    4
  • Abstract
    An adaptive neuro-fuzzy inference system (ANFIS) based method is proposed for speckle noise reduction in synthetic aperture radar (SAR) images. Before using active RADAR (radio detection and ranging) and SAR imageries, the very first step is to reduce the effect of speckle noise. Reduction of speckle noise is one of the most important processes to increase the quality of radar coherent images. Filtering is the common method which is used to reduce the speckle noise. For this purpose, two ANFISs are trained and outputs of these systems are converted to one output through a mean calculator in this work. Performance of the proposed method is compared with performances of state-of-the-art methods in the literature for speckle noise reduction. Results are presented by filtered images and a table.
  • Keywords
    fuzzy neural nets; fuzzy reasoning; image denoising; radar imaging; speckle; synthetic aperture radar; ANFIS; SAR images; active RADAR image; adaptive neuro-fuzzy inference system; radar coherent images; speckle noise reduction; synthetic aperture radar images; Adaptive optics; Adaptive systems; Image converters; Noise reduction; Optical surface waves; Radar imaging; Radar remote sensing; Remote sensing; Speckle; Synthetic aperture radar;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Signal Processing and Its Applications, 2007. ISSPA 2007. 9th International Symposium on
  • Conference_Location
    Sharjah
  • Print_ISBN
    978-1-4244-0778-1
  • Electronic_ISBN
    978-1-4244-1779-8
  • Type

    conf

  • DOI
    10.1109/ISSPA.2007.4555350
  • Filename
    4555350